Many species rely on acoustic communication to fulfil several functions such as advertisement and mediation of social interactions (e.g., agonistic, mating). Therefore, fish calls can be an important source of information, e.g., to recognize reproductive periods or to assess fish welfare, and should be considered a potential non-intrusive tool in aquaculture management. Assessing fish acoustic activity, however, often requires long sound recordings. To analyse these long recordings automatic methods are invaluable tools to detect and extract the relevant biological information. Here we present a study to characterize meagre (Argyrosomus regius
) acoustic activity during social contexts in captivity using an automatic pattern-recognition methodology based on the Hidden Markov Model. Calls produced by meagre during the breading season showed a richer repertoire than previously reported. Besides the dense choruses composed by grunts already known for this species, meagre emitted successive series of isolated pulses, audible as ‘knocks’. Grunts with a variable number of pulses were also registered. The overall acoustic activity was concurrent with the number of spawning events. A diel call rhythms exhibit peak of calling activity from 15:00 to midnight. In addition, grunt acoustic parameters varied significantly along the reproduction season. These results open the possibility to use the meagre vocal activity to predict breeding and approaching spawning periods in aquaculture management.
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